The Virtual Functional Anatomy project is designed to fill the important knowledge gap that exists between the relationship of normal or impaired joint structure/function and the functional movement limitations associated with performing activities of daily living. Our current focus is to develop and ultimately validate a combined set of tools that will enable the accurate and precise measurement, analysis and visualization of three-dimensional (3-D) static and dynamic musculoskeletal anatomy (i.e., bone shape, skeletal kinematics, tendon and ligament strain, muscle force, and joint space). We plan to combine MRI imaging and analysis capabilities with a highly accurate, imaging-based measurement and analysis technique for the non-invasive quantification of complete joint anatomy and tissue dynamics during functional movements. This will require the development of a method for creating 3D digital images of loaded and moving joint tissues (bone, cartilage, and connective tissues) to reveal joint contact patterns and tissue loads. We will also evaluate the variability of bone shape and the sensitivity of defined joint posture (translation and rotation of one bone relative to another) to osteo-based coordinate system definition. We intend to use these capabilities to document and evaluate the function of normal and impaired joint structures (e.g., ACL rupture and patellar tracking syndrome) under simulated conditions experienced during activities of daily living. Recently, this work has concentrated on two primary project areas: 1) VFA tool development and 2) In vivo normal and impaired knee joint function. VFA Tool Development Over the past year, we have maintained a research focus on developing the backbone for VFA and began to explore the issues surrounding the dynamic MR scanning of the musculoskeletal system. The key focal points for the algorithm development were the image registration process along with continuing improvement in the integration algorithms.. Fast-PC MRI can provide 3D kinematics information for the bones of a joint (e.g., knee and ankle) as the subject brings this joint through a specified range of motion. Yet, this information cannot be readily applied to 3D models of the bones, which are created from static high-resolution scans of the joint. In order to apply the kinematics from the fast-PC MRI to the static models, the two image data sets have to be aligned (e.g., registered). Visualization is made possible by programs that have been written in-house using Matlab?s scripting language. This registration process led to the first dynamic cartilage contact model, measured non-invasively and in vivo, being developed this year. In Vivo Normal and Impaired Knee Joint Function On the experimental side, a primary focus has been on evaluating the clinical applicability of the tools being developed by applying them to children and adults diagnosed with Cerebral Palsy (n=7) Ehlers Danlos syndrome (n=6), stroke (n=1) and patellofemoral pain syndrome (n=1). We are in the process of analyzing the data acquired in order to quantify the various musculoskeletal parameters, such as joint kinematics, tendon strains, and tendon moment arms. As we complete the VFA toolbox, we should also be able to quantify forces in the quadriceps muscles, patellar tendon, the anterior cruciate ligament, and the cartilage during an extension/flexion cycle of the knee joint. Since the forces in the muscles are being calculated by measuring the strain in the tendons, it is imperative that errors be minimized during this measurement. Thus, in the normative population we are maximizing the strain within the tendons by maximizing the load being raised in extension, through the use of non-magnetic ankle weights. We are currently conducting a study to test the maximum weight that can be used without disrupting the repeatability of the motion. Moving forward, there are three major focus areas for this project. The first is to quantify healthy knee joint dynamics during loaded tasks that mimic functional activities of daily living. These data will then be compared to the knee joint dynamics of impaired subjects. The second project is similar, in that we are quantifying the 3D kinematics of the bones of the ankle joint during loaded tasks mimicking functional activities of daily living. Lastly, we are continue to progress towards improvements in imaging time and data accuracy through algorithm and image sequence development.